def test_labels(self, verify):
values = [3, 1, 2, 0, 4]
expected = np.array([0, 1, 2, 3, 4])
labels = [0, 1, 1, 2, 3, 0, -1, 4]
result, result_labels = safe_sort(values, labels, verify=verify)
expected_labels = np.array([3, 1, 1, 2, 0, 3, -1, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
# na_sentinel
labels = [0, 1, 1, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(values,
labels,
na_sentinel=99,
verify=verify)
expected_labels = np.array([3, 1, 1, 2, 0, 3, 99, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
labels = []
result, result_labels = safe_sort(values, labels, verify=verify)
expected_labels = np.array([], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_labels(self):
values = [3, 1, 2, 0, 4]
expected = np.array([0, 1, 2, 3, 4])
labels = [0, 1, 1, 2, 3, 0, -1, 4]
result, result_labels = safe_sort(values, labels)
expected_labels = np.array([3, 1, 1, 2, 0, 3, -1, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
# na_sentinel
labels = [0, 1, 1, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(values, labels,
na_sentinel=99)
expected_labels = np.array([3, 1, 1, 2, 0, 3, 99, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
# out of bound indices
labels = [0, 101, 102, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(values, labels)
expected_labels = np.array([3, -1, -1, 2, 0, 3, -1, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
labels = []
result, result_labels = safe_sort(values, labels)
expected_labels = np.array([], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_labels(self):
values = [3, 1, 2, 0, 4]
expected = np.array([0, 1, 2, 3, 4])
labels = [0, 1, 1, 2, 3, 0, -1, 4]
result, result_labels = safe_sort(values, labels)
expected_labels = np.array([3, 1, 1, 2, 0, 3, -1, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
# na_sentinel
labels = [0, 1, 1, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(values, labels,
na_sentinel=99)
expected_labels = np.array([3, 1, 1, 2, 0, 3, 99, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
# out of bound indices
labels = [0, 101, 102, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(values, labels)
expected_labels = np.array([3, -1, -1, 2, 0, 3, -1, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
labels = []
result, result_labels = safe_sort(values, labels)
expected_labels = np.array([], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_unsortable(self):
# GH 13714
arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
msg = ("unorderable types: .* [<>] .*"
"|" # the above case happens for numpy < 1.14
"'[<>]' not supported between instances of .*")
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
def test_unsortable(self):
# GH 13714
arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
msg = ("unorderable types: .* [<>] .*"
"|" # the above case happens for numpy < 1.14
"'[<>]' not supported between instances of .*")
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
def test_unsortable(self):
# GH 13714
arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
msg = (r"'(<|>)' not supported between instances of ('"
r"datetime\.datetime' and 'int'|'int' and 'datetime\.datetime"
r"')|"
r"unorderable types: int\(\) > datetime\.datetime\(\)")
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
def test_unsortable(self):
# GH 13714
arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
msg = (
r"unorderable types: ({0} [<>] {1}|{1} [<>] {0})".format(
r"int\(\)", r"datetime\.datetime\(\)") # noqa: E126
if _np_version_under1p14 else
(r"'[<>]' not supported between instances of "
r"({0} and {1}|{1} and {0})").format("'int'",
r"'datetime\.datetime'"))
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
def test_pairwise_with_other(self, f):
# DataFrame with another DataFrame, pairwise=True
results = [f(df, self.df2) for df in self.df1s]
for (df, result) in zip(self.df1s, results):
tm.assert_index_equal(result.index.levels[0], df.index, check_names=False)
tm.assert_numpy_array_equal(
safe_sort(result.index.levels[1]), safe_sort(self.df2.columns.unique())
)
for i, result in enumerate(results):
if i > 0:
self.compare(result, results[0])
def test_mixed_integer(self):
values = np.array(['b', 1, 0, 'a', 0, 'b'], dtype=object)
result = safe_sort(values)
expected = np.array([0, 0, 1, 'a', 'b', 'b'], dtype=object)
tm.assert_numpy_array_equal(result, expected)
values = np.array(['b', 1, 0, 'a'], dtype=object)
labels = [0, 1, 2, 3, 0, -1, 1]
result, result_labels = safe_sort(values, labels)
expected = np.array([0, 1, 'a', 'b'], dtype=object)
expected_labels = np.array([3, 1, 0, 2, 3, -1, 1], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_mixed_integer(self):
values = np.array(['b', 1, 0, 'a', 0, 'b'], dtype=object)
result = safe_sort(values)
expected = np.array([0, 0, 1, 'a', 'b', 'b'], dtype=object)
tm.assert_numpy_array_equal(result, expected)
values = np.array(['b', 1, 0, 'a'], dtype=object)
labels = [0, 1, 2, 3, 0, -1, 1]
result, result_labels = safe_sort(values, labels)
expected = np.array([0, 1, 'a', 'b'], dtype=object)
expected_labels = np.array([3, 1, 0, 2, 3, -1, 1], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_unsortable(self):
# GH 13714
arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
msg = ("'<' not supported between instances of 'datetime.datetime'"
r" and 'int'|"
r"unorderable types: int\(\) > datetime.datetime\(\)")
if compat.PY2:
# RuntimeWarning: tp_compare didn't return -1 or -2 for exception
with warnings.catch_warnings():
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
else:
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
def test_unsortable(self):
# GH 13714
arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
msg = (r"'(<|>)' not supported between instances of ('"
r"datetime\.datetime' and 'int'|'int' and 'datetime\.datetime"
r"')|"
r"unorderable types: int\(\) > datetime\.datetime\(\)")
if compat.PY2:
# RuntimeWarning: tp_compare didn't return -1 or -2 for exception
with warnings.catch_warnings():
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
else:
with pytest.raises(TypeError, match=msg):
safe_sort(arr)
def test_basic_sort(self):
values = [3, 1, 2, 0, 4]
result = safe_sort(values)
expected = np.array([0, 1, 2, 3, 4])
tm.assert_numpy_array_equal(result, expected)
values = list("baaacb")
result = safe_sort(values)
expected = np.array(list("aaabbc"), dtype='object')
tm.assert_numpy_array_equal(result, expected)
values = []
result = safe_sort(values)
expected = np.array([])
tm.assert_numpy_array_equal(result, expected)
def test_basic_sort(self):
values = [3, 1, 2, 0, 4]
result = safe_sort(values)
expected = np.array([0, 1, 2, 3, 4])
tm.assert_numpy_array_equal(result, expected)
values = list("baaacb")
result = safe_sort(values)
expected = np.array(list("aaabbc"), dtype='object')
tm.assert_numpy_array_equal(result, expected)
values = []
result = safe_sort(values)
expected = np.array([])
tm.assert_numpy_array_equal(result, expected)
def test_extension_array(self):
# a = array([1, 3, np.nan, 2], dtype='Int64')
a = array([1, 3, 2], dtype='Int64')
result = safe_sort(a)
# expected = array([1, 2, 3, np.nan], dtype='Int64')
expected = array([1, 2, 3], dtype='Int64')
tm.assert_extension_array_equal(result, expected)
def test_extension_array(self):
# a = array([1, 3, np.nan, 2], dtype='Int64')
a = array([1, 3, 2], dtype='Int64')
result = safe_sort(a)
# expected = array([1, 2, 3, np.nan], dtype='Int64')
expected = array([1, 2, 3], dtype='Int64')
tm.assert_extension_array_equal(result, expected)
def test_extension_array_labels(self, verify, na_sentinel):
a = array([1, 3, 2], dtype='Int64')
result, labels = safe_sort(a, [0, 1, na_sentinel, 2],
na_sentinel=na_sentinel, verify=verify)
expected_values = array([1, 2, 3], dtype='Int64')
expected_labels = np.array([0, 2, na_sentinel, 1], dtype=np.intp)
tm.assert_extension_array_equal(result, expected_values)
tm.assert_numpy_array_equal(labels, expected_labels)
def test_pairwise_with_self(self, f):
# DataFrame with itself, pairwise=True
# note that we may construct the 1st level of the MI
# in a non-monotonic way, so compare accordingly
results = []
for i, df in enumerate(self.df1s):
result = f(df)
tm.assert_index_equal(result.index.levels[0], df.index, check_names=False)
tm.assert_numpy_array_equal(
safe_sort(result.index.levels[1]), safe_sort(df.columns.unique())
)
tm.assert_index_equal(result.columns, df.columns)
results.append(df)
for i, result in enumerate(results):
if i > 0:
self.compare(result, results[0])
def test_extension_array_labels(self, verify, na_sentinel):
a = array([1, 3, 2], dtype='Int64')
result, labels = safe_sort(a, [0, 1, na_sentinel, 2],
na_sentinel=na_sentinel,
verify=verify)
expected_values = array([1, 2, 3], dtype='Int64')
expected_labels = np.array([0, 2, na_sentinel, 1], dtype=np.intp)
tm.assert_extension_array_equal(result, expected_values)
tm.assert_numpy_array_equal(labels, expected_labels)
def test_labels_out_of_bound(self, na_sentinel):
values = [3, 1, 2, 0, 4]
expected = np.array([0, 1, 2, 3, 4])
# out of bound indices
labels = [0, 101, 102, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(values, labels, na_sentinel=na_sentinel)
expected_labels = np.array(
[3, na_sentinel, na_sentinel, 2, 0, 3, na_sentinel, 4], dtype=np.intp
)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_labels_out_of_bound(self, na_sentinel):
values = [3, 1, 2, 0, 4]
expected = np.array([0, 1, 2, 3, 4])
# out of bound indices
labels = [0, 101, 102, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(
values, labels, na_sentinel=na_sentinel)
expected_labels = np.array(
[3, na_sentinel, na_sentinel, 2, 0, 3, na_sentinel, 4],
dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_labels(self, verify):
values = [3, 1, 2, 0, 4]
expected = np.array([0, 1, 2, 3, 4])
labels = [0, 1, 1, 2, 3, 0, -1, 4]
result, result_labels = safe_sort(values, labels, verify=verify)
expected_labels = np.array([3, 1, 1, 2, 0, 3, -1, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
# na_sentinel
labels = [0, 1, 1, 2, 3, 0, 99, 4]
result, result_labels = safe_sort(values, labels, na_sentinel=99,
verify=verify)
expected_labels = np.array([3, 1, 1, 2, 0, 3, 99, 4], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
labels = []
result, result_labels = safe_sort(values, labels, verify=verify)
expected_labels = np.array([], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
tm.assert_numpy_array_equal(result_labels, expected_labels)
def test_exceptions(self):
with pytest.raises(TypeError, match="Only list-like objects are allowed"):
safe_sort(values=1)
with pytest.raises(TypeError, match="Only list-like objects or None"):
safe_sort(values=[0, 1, 2], labels=1)
with pytest.raises(ValueError, match="values should be unique"):
safe_sort(values=[0, 1, 2, 1], labels=[0, 1])
def test_exceptions(self):
with tm.assert_raises_regex(TypeError,
"Only list-like objects are allowed"):
safe_sort(values=1)
with tm.assert_raises_regex(TypeError,
"Only list-like objects or None"):
safe_sort(values=[0, 1, 2], labels=1)
with tm.assert_raises_regex(ValueError, "values should be unique"):
safe_sort(values=[0, 1, 2, 1], labels=[0, 1])
def test_exceptions(self):
with tm.assert_raises_regex(TypeError,
"Only list-like objects are allowed"):
safe_sort(values=1)
with tm.assert_raises_regex(TypeError,
"Only list-like objects or None"):
safe_sort(values=[0, 1, 2], labels=1)
with tm.assert_raises_regex(ValueError,
"values should be unique"):
safe_sort(values=[0, 1, 2, 1], labels=[0, 1])
def test_exceptions(self):
with pytest.raises(TypeError,
match="Only list-like objects are allowed"):
safe_sort(values=1)
with pytest.raises(TypeError,
match="Only list-like objects or None"):
safe_sort(values=[0, 1, 2], labels=1)
with pytest.raises(ValueError,
match="values should be unique"):
safe_sort(values=[0, 1, 2, 1], labels=[0, 1])
def test_mixed_integer_from_list(self):
values = ['b', 1, 0, 'a', 0, 'b']
result = safe_sort(values)
expected = np.array([0, 0, 1, 'a', 'b', 'b'], dtype=object)
tm.assert_numpy_array_equal(result, expected)
def test_mixed_integer_from_list(self):
values = ['b', 1, 0, 'a', 0, 'b']
result = safe_sort(values)
expected = np.array([0, 0, 1, 'a', 'b', 'b'], dtype=object)
tm.assert_numpy_array_equal(result, expected)
